Cytomorphometry of Fine Needle Biopsy Material from the Breast Cancer

Marciniak, Andrzej; Obuchowicz, Andrzej; Monczak, Roman; Kołodziński, Mariusz

doi:10.1007/3-540-32390-2_71

Cited by 17 publications

(9 citation statements)

References 2 publications

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“…The material was collected from 75 patients of the Regional Hospital in Zielona Góra. It gives 10 images per case which was the recommended amount by the specialists from the hospital [5,9] and allows for a correct diagnosis by a pathologist. The set contains 25 benign, 25 malignant and 25 fibroadenoma cases.…”

Section: Medical Images Databasementioning

confidence: 99%

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Breast fibroadenoma automatic detection using k-means based hybrid segmentation method

Filipczuk

Kowal

Obuchowicz

2012

2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)

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Fibroadenoma is a benign tumor that has some features similar to a malignant one. The aim of this study was to examine the impact of fibroadenoma cases on the results of the automatic breast cancer diagnostic system based on the quantitative morphometric analysis of fine needle biopsy microscopic images. The database of 50 patients (500 images) of benign and malignant lesions used previously in our research was enriched by an additional 25 patients (250 images) of fibroadenoma cases. Experiments were performed using the k-means based hybrid segmentation method. The system was tested on a set of real case medical images with promising results.

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Section: Medical Images Databasementioning

confidence: 99%

“…In literature, there have been many different approaches presented to extract cells from microscope images [10,11,12,5,6,7,9,13]. This task is usually done automatically, using one of the well known methods of image segmentation [14,15].…”

Section: Automatic Diagnosis Proceduresmentioning

confidence: 99%

Breast fibroadenoma automatic detection using k-means based hybrid segmentation method

Filipczuk

Kowal

Obuchowicz

2012

2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)

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“…What we have on input is cytological material obtained using the Fine Needle Biopsy (FNB) technique and imagined with a Sony CCD Iris camera mounted on top of an Axiophot microscope. The material comes from female patients of the Onkomed medical center in Zielona Góra (Marciniak et al, 2005). The image itself is coded using the RGB colorspace and is not subject to any kind of lossy compression (a raw color bitmap format).…”

Section: Problem Formulationmentioning

confidence: 99%

Segmentation of Breast Cancer Fine Needle Biopsy Cytological Images

Hrebień

Stec

Nieczkowski

et al. 2008

International Journal of Applied Mathematics and Computer Science

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This paper describes three cytological image segmentation methods. The analysis includes the watershed algorithm, active contouring and a cellular automata GrowCut method. One can also find here a description of image pre-processing, Hough transform based pre-segmentation and an automatic nuclei localization mechanism used in our approach. Preliminary experimental results collected on a benchmark database present the quality of the methods in the analyzed issue. The discussion of common errors and possible future problems summarizes the work and points out regions that need further research.

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“…What we have on input is a cytological material obtained using the Fine Needle Biopsy technique and imagined with a Sony CCD Iris camera mounted atop of an Axiophot microscope. The material comes from female patients of Zielona Góra's Onkomed medical center (Marciniak et al, 2005). The 704 × 576 pixel image itself is coded using the RGB colourspace and is not subject of any kind of lossy compression.…”

Section: Problem Formulationmentioning

confidence: 99%

Comparison of Fine Needle Biopsy Cytological Image Segmentation Methods

Hrebień¹,

Stec²,

Korbicz³

2007

Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics

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This paper describes an early stage of cytological image recognition and presents a comparision of two hybrid segmentation methods. The analysis includes the Hough transform with conjunction to the watershed algorithm and with conjunction to the active contours techniques. One can also find here a short description of image pre-processing and an automatic nucleuses localization mechanisms used in our approach. Preliminary experimental results collected on a hand-prepared benchmark database are also presented with short discussion of common errors and possible future problems.

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Cytomorphometry of Fine Needle Biopsy Material from the Breast Cancer

Cited by 17 publications

References 2 publications

Breast fibroadenoma automatic detection using k-means based hybrid segmentation method

Breast fibroadenoma automatic detection using k-means based hybrid segmentation method

Segmentation of Breast Cancer Fine Needle Biopsy Cytological Images

Comparison of Fine Needle Biopsy Cytological Image Segmentation Methods

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